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Field
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statistical analysis of proteomic, phosphoproteomic and related multi omics datasets. The role will contribute to the School's research activity by developing robust, reproducible analytical workflows
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environments; experience coordinating complex workflows (e.g., between wet lab, proteomics and dry lab) and maintaining structured project documentation. The lab places strong emphasis on teamwork, where
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. Current research areas include environmental and lifestyle exposures, metabolic dysfunction, obesity, inflammation, proteomics, metabolomics, and other multi-omics approaches in relation to cancer and
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research environment with broad expertise including cardiac, cellular biophysics, imaging, aging, and proteomics. PI commitment to mentoring and career development opportunities tailored to allow
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modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics, and metabolomics. Working closely with senior
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and Statistics. The School of Mathematics and Statistics is seeking to appoint a Postdoctoral Researcher for a 4-month role to support the bioinformatic and statistical analysis of proteomic
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proteomics, structural biology, and molecular biology to define new modes of GPCR signaling. We are particularly interested in candidates with strong backgrounds in proteomics and/or structural biology and/or
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technologies for transcriptomic, proteomic, and metabolomic studies. Complete the assigned work in time. Complete complex research projects at different stages (advanced through nearly completed). Formulate
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largely unexplored layer of organelle regulation. By integrating subcellular transcriptomics, selective ribosome profiling, proteomics, and structural approaches, we aim to define the ciliary transcriptome
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. Candidates with experience in genomic analyses, proteomic approaches, imaging analysis, iPS differentiation and bioinformatics would be especially welcome. The post available as a fixed-term contract for 1